International material resource dependency in an international input-output framework*

Transcription

1 Paper to be presented at the IIOA conference, June 2010, Sydney, Australia International material resource dependency in an international input-output framework* Bouwmeester, Maaike C. a# ; Oosterhaven, Jan a a University of Groningen, Faculty of Economics and Business Postbus 800, 9700 AV Groningen, The Netherlands Abstract Over the last decade an increasing awareness of resources embodied in traded products has resulted in attempts to track natural resource use along the international supply chain. An international input-output (IIO) model is the appropriate methodological framework to undertake this type of environmental accounting, because direct and indirect, domestic and international resource use is considered. However, an extensive IIO model capturing most of world trade has vast data requirements. As indicated by Wiedmann (2009) there is still room for improvements in data availability and quality. The EU-funded EXIOPOL project provides this opportunity through its environmentally extended international input-output database. This database, containing domestic and international trade flows of 43 countries, is essential for estimating the actual environmental impacts of international production and consumption. The project has an important role in delivering the desired improvements. In this study we analyze resource use and dependence among the 43 counties present in the EXIOPOL. Our focus will be on fossil fuel carriers, metals and mineral resource use. Keywords: international input-output, environmental accounting, resources, dependency Areas submitted to: 1. International Input-Output and Supply-Use models # Corresponding author: Phone Fax m.c.bouwmeester@rug.nl * The title and abstract deviate from the submitted title and abstract due to delays in the project.

2 1. Introduction Over the past decade environmentally extended input output tables (EE IOT) have received much attention due to their usefulness as data source for environmental accounting. Input-output tables and the related models allow for calculating the direct and indirect effects of an increase in final demand on total output. Extending input-output tables with environmental information results in a framework that is very suitable for analyzing the relationship between economic activities and the pressure on the environment caused by these activities. The incorporated environmental information can consist of, for example, pollution generated or resources used. Many policy analyses based on input-output analysis are still performed using national tables. The implicit assumption made in these analyses is that the national structure may also be used to estimate the international spillovers of national measures. The vast data requirement of international input-output tables has been one of the main reasons for this practice. However, since the 1950s, international trade has been increasing steadily 1. Within the European Union trade has expanded even more due to the internal market, which came into being in 1993 and the monetary union in which 16 European countries now participate. Over the years only few inputoutput tables have been constructed that include international trade flows among (the most important) trade partners. These are the European Union intercountry input-output tables (Linden & Oosterhaven, 1995), the Asian-Pacific international input-output tables (Inomata & Okamoto, 2006) and are the GTAP database (Dimaranan, 2006). Including international trade linkages is aimed at in order to be able to analyze international integration and the dependency of production. International input-output tables allow, for example, tracking the economic impacts of changes in final demand for products across borders. The combination of environmentally extended input-output tables and international trade flows provides a strong basis for environmental policy analysis. Such an elaborate framework offers the opportunity to undertake environmental accounting in a complete economic transaction system. For example, it can be established whether the Japanese cars contain more or less material resources than cars produced in the United States. In addition, it can be investigated which countries actually mine these resources. Alternatively, it can be analyzed for how much CO 2 emission the Dutch government is responsible, compared to Dutch consumers and whether these are emitted domestically or abroad, and where in the latter case. 1 A decline in trade flows occurred in 2009 due to the crisis. 2

3 An important application of international EE IOT is the accounting of pollution generated and resources used in terms of producer versus consumer responsibility. A national EE IOT only allows for calculating the environmental impacts due to production of domestic industries. The incorporation of trade flows in EE IOT makes it possible to track where products consumed in a country are produced and what are the related pollution generated or resources used. In this light, it is debatable whether China is responsible for the pollution it generates or the countries to which the products are exported to by China. Important methodological work to incorporate EE IOT in the standard toolbox of environmental policy makers has been undertaken in various projects. Without exception, it is stressed in these projects that the database used for analysis has to include international trade flows. The final report of the EIPOT 2 project presents a methodological toolbox that is developed to assess environmental impacts through international trade (Wiedmann et al., 2008). The report indicates that the ideal basis for a suitable methodology in this context would be an environmentally extended multi-region input-output framework with close connections to the system of economic and environmental accounts as developed by the United Nations. 3 It includes very specific recommendations regarding the set up of the accounting framework. In an earlier project, a report was published to convey the data situation of EE IOT (Eder et al., 2006). In order to stress the importance of EE IOT in terms of availability and quality, the full potential of the tables is explored and principal application areas are discussed. In addition, given the analytical requirements of the applications, the technical specifications of the required data are defined and options for acquiring the data are given. In a review of the multi-region IOT used in environmental accounting (Wiedmann, 2009) concludes that further research is mainly needed in order to improve data availability, data quality, and accuracy of multi-region input output modeling. (Lenzen, Pade, & Munksgaard, 2004) compare the implications of using alternative trade models and of a reduction in detail in the sectoral disaggregation of the tables. It is shown that especially aggregation of high with low impacting sectors causes problems. In terms of trade relations, the study suggest that including direct import use coefficients is most important in correctly assigning environmental impacts of production of a specific country. 2 Environmental impacts of trade, see also the website where the final report can be downloaded, last accessed See for more information. 3

4 The construction of a multi-regional EE IOT database that incorporates the recommendations made in the literature is undertaken in the EXIOPOL project. 4 The project has been set up to provide a new environmental accounting framework for policy analysis, using externality data and input-output tools. The objective of the project is to enable the estimation of environmental impacts and external costs of industry activities and consumption activities of countries in the European Union. These environmental impacts include greenhouse gases emitted, pollutants discarded, and resources used as inputs to production. Within the project methodologies are developed, valuation of externalities is undertaken, and an environmentally extended (EE) input-output (IO) framework is set up that the European Union can use for environmental policy analysis (Tukker et al., 2009). The EXIOPOL database, which has as core an environmentally extended IO framework, will contain satellite accounts for more than one hundred environmental factors. The focus on the environment also called for more detail in the sectors that are mostly involved in generating or using these environmental factors. Agriculture, food products, mining and energy have been disaggregated into multiple subsectors. By covering around 80 percent of world GDP, adding sectoral detail and the incorporation of bilateral trade, the EXIOPOL database caters directly for the need of harmonized and improved data for EE IOT analysis. The EXIOPOL database is in its final stages of development. Although work is progressing steadily, the country SUT data is still under revision and not all environmental extensions are available yet. In this paper a first preliminary analysis is undertaken based on the data that is available at this point in time. The focus of the present analysis is on metals, minerals, and fossil energy carriers. In particular, we will first address for which countries and sectors an increase in final demand generates the most additional extraction of the three types of resources. This indicates the dependency of a sector on material resources. Second, we investigate the extent to which this additional demand is generated in other countries, which shows how dependent a country is on foreign suppliers of the material resources. Next, the concentration of the international dependency is analyzed as an important aspect of the factual dependency. A correlation analysis is undertaken to see to what extent these three measures are related for individual sectors. 4 EXIOPOL is the acronym for: a new environmental accounting framework using externality data and input-output tools for policy analysis. The project website is last accessed

5 Unlike capital that can be accumulated or population that can increase, natural resources cannot be produced. In case a country is not endowed with natural resources, it will need to obtain the resources needed for production through international trade. This can be done by either importing the natural resources directly from another country or by importing intermediate inputs in which these resources are embodied. Unstable economic trade relations with a country that is a primary supplier of the natural resources needed to fulfill a country s final demand may be harmful to the economy. Fully depending on other countries for the supply of natural resources has been viewed as undesirable, especially after the two main oil crises of the 20 th century and the increasing scarcity of fossil energy carriers. A strategy of diversifying imports over the countries which have natural resource endowments may decreases risks associated with natural resource dependency. In the next sections the methods used are discussed followed by a description of the data available from the EXIOPOL database. Then, the first results on environmental resource dependency are presented. To conclude, the preliminary status of this paper is stressed by discussing the next steps that will be taken when the database is finalized. 2. Methods The derivation of an input-output model from a SUT requires an explicit assumption regarding the production technology of secondary and/or by-products of industries, whereas this assumption is hidden in input-output tables. Different assumptions can be made and there is no definite answer to the question which of these is conceptually and practically the best. For the results calculated here the industry technology assumption has been used to create an industry by industry IOT. ( ) ( ) 1 1 A ˆ ˆ ixi, ind tech = V q U x 1 Where V is the transposed supply table, q is the total supply of products, U is the use matrix and x is the total output of domestic industries. The hat over the variables indicates a diagonalized matrix. An input-output model describes how supply x follows demand with the following identity: x = Ax + f. Where x is total output, A the matrix of direct input coefficients and f the vector of final demand. Solving the model for output gives = ( ) 1 x I A f, where (I A) -1 is the Leontief multiplier matrix of direct and indirect industry output requirements per unit of final 5

6 demand. In the Leontief quantity model, from which the backward multipliers are derived, the assumption is made that prices are fixed in the short term. Another assumption in IO modeling is that input coefficients do not change regardless of output, final demand, or other relevant changes. The structure of the economy is taken to be constant, at least in the short term. The environmental extensions are given as a matrix of direct impact coefficients D = [ ], of which each element represents the amount (in physical units per d kj dollar s worth of output) of the environmental factor k used in the production of sector j. These environmental extensions can be emissions, pollution, raw material, land use, water use, etc. The total requirement of environmental factors E x can be calculated as: E 1 x = Dx = D( I A) f 2 For an international input-output table the same equation 2 holds, where x is now a vector of all individual country sub vectors R x, for all countries R. The matrix D = [ ] is the concatenated R d kj matrix of all individual country matrices RS D. The matrix A = [ ] is the input coefficient R a ij matrix of all domestic RR A matrices and all bilateral matrices RS A, where R and S are the country indices and i and j are sector indices. The vector f is the stacked vecotr of all individual country final demand vectors f R. The total requirement of environmental factors E x signifies the dependency of a sector on material resource inputs. The requirements may be partially sourced domestically, but especially for the countries that do are not endowed with material resources, these requirements will be imported. The extent of dependency on foreign suppliers for material resources is measured by the requirement of imported environmental factors over the total requirement. In addition, the Herfindahl index will be used to look at the concentration of the environmental requirements over the countries from which a sector imports. This highlights an important aspect of dependency; importing from multiple sources will make a country less dependent on one particular supplier. The index can be represented as given by equation 3, where k is the index representing the different resources. H 2 3 d l = R RS ki ij S i kj R RS R S dkil ij i, R S 6

7 Each country has potentially 41 trading partners. For 41 observations, the value of the Herfindahl index would equal to 1/ in case each of the environmental multipliers is exactly the same for each trade partner. This corresponds to full diversification over countries from which a particular country demands its imports and embodied resources. When a country only imports the embodied resources from one trade partner the value of the Herfindahl index will be equal to 1. The higher the value of the Herfindahl index the more dependent a country is on one, or a few countries, to fulfill its demand for embodied materials. 3. Data The full EXIOPOL database consists of the supply and use tables (SUT) of 43 countries 5 and an aggregated rest of the world. The supply and use tables maintained by Eurostat (referred to as the ESA-95 tables) are used as basis for the supply and use tables of the European Union countries. These tables have been disaggregated in industry and commodity classification to 129 industries and products, still in a squared set-up of the SUT. The tables are linked to each other via bilateral trade flows using a methodology that combines information on origin and destination of trade flows from trade statistics with the aggregated trade data in the SUT. In the process of regaining consistency after combining these two data sources, the data are also revalued from cost-insurance-freight prices of the purchasing country to basic prices of the producing country. (For a full description of the methodology see (Bouwmeester & Oosterhaven, 2008). It has to be noted that although several information sources are combined to construct a full international SUT, these tables do not represent full information. All supply and use tables are extended with satellite accounts of social and environmental variables. The database also contains input-output tables that have resulted from input-output modeling of the supply and use tables. See chapter 5 of Miller & Blair (1984), for an explanation of the assumptions that need to be made in IO modeling. All data used in this analysis is taken from the preliminary versions of data that will be part of the EXIOPOL database. Due to some remaining problems in the sectors that have been disaggregated up to this point, the SUT have been aggregated back to the 59 sectors as represented in the ESA-95 tables. In addition, due to problems with the data of Estonia this 5 See the appendix tables for a full list of the countries included. 7

8 country is removed from the dataset. For some sectors environmental extensions are present for a certain sector, while there is no output in the SUT. These environmental extensions are therefore disregarded in the analysis. The environmental extensions used in this study are: 1) domestic extraction of metal ores 6, 2) domestic extraction of non-metallic minerals 7, and 3) fossil energy carriers Results and discussion In this section an analysis is presented of the dependency of countries on trade partners to fulfill their demand for embodied materials. First, we will have a closer look at the countries that supply resources. Next, to focus the discussion of the results, we selected the industries that on a world scale demand the most additional resources per of output. For this purpose we have created a world weighted average supply and use table and a vector with the total material use per world sector. For these selected industries we computed the share of the international environmental multiplier in the total environmental multiplier as a measure of dependency on trade partners to fulfill the demand for embodied resources. Next, we also look at the Herfindahl index of the international multipliers to determine the concentration of dependency. Finally, a correlation analysis is undertaken to see whether higher international dependence of countries is related to a higher concentration of international dependence. This would indicate that the sector may be very vulnerable to the effects of increasing scarcity of material resources. Not all countries are suppliers of material resources. It may be that the materials are not present at all in the soil on a country s territory. Alternatively, it may be that there are material resources, but only in a limited amount or hard to retrieve, making it economically uninteresting to mine the materials. For fossil fuels, the following countries do not mine coal or extract oil or gas; Belgium, Cyprus, Ireland, Luxembourg, Malta, Portugal and Switzerland. Metals are not mined in the countries: Austria, Belgium, Czech Republic, Denmark, Germany, Latvia, Lithuania, 6 Which consist of: iron ores, bauxite and aluminum ores, copper ores, lead ores, nickel ores, tin ores, zinc ores, precious metal ores and other metal ores. Note that uranium and thorium ores have been excluded, because their nature deviates from the other metals; these ores are mainly used as fuel. 7 Which consist of: chemical and fertilizer minerals, clays and kaolin, limestone, gypsum, chalk, dolomite, salt, slate, other industrial minerals, building stones, gravel and sand, other construction materials 8 Which consist of: hard coal, lignite/brown coal, crude oil, natural gas, natural gas liquids, peat for energy use. 9 Unused domestic extraction related to these materials is not included in the analysis. 8

9 Luxembourg, Malta, Netherlands, Slovenia, Switzerland, Taiwan and United Kingdom. For minerals only Poland has no reported output for the mineral sector, however, the environmental extensions do report a large amount of minerals extracted, so this may be a flaw in the supply and use tables. Summarizing; 35 countries extract fossil fuels, metal ores are mined in 28 countries and 41 countries report output for their mineral sector. In Table 1, the top three of countries with the most domestic extraction used, as well as the top three of countries with the most material use per million output are represented. 10 Invariably, the United States is the largest extractor of materials, however its ranking in terms of the use of materials per euro demand is for fossil fuel 13 th,, for metals 6 th and for minerals 12 th. Fossil fuel carriers Table 1: Domestic extraction used million tonnes Fossil fuel carriers kilogram per output 1 United States Hungary China Greece Russian Federation Bulgaria Metal ores Metal ores 1 United States Bulgaria Australia France Indonesia India Minerals Minerals 1 United States Sweden China Latvia Japan Taiwan Due to the large amount of sectors; 59 sectors in each of the 42 countries included in the dataset, we have chosen to focus our analysis to the sectors that have the highest resource use per of demand for that sectors output. See Table 2 for the ranking of the industries and the related value of the environmental multiplier for each of the material groups considered. See Appendix 1 for the sector classification codes and labels. For each material group the sector which mines or extracts that resource is associated to the largest environmental multiplier. Fossil fuel carriers are extracted by sector i10 and sector i11. More interesting are the sectors in the table that are not directly related to the mining of the material resources. In Appendix 2 Table 2 the detailed breakdown of the environmental multipliers per country can be found. 10 See Appendix 2, Table 1 for the table of resource use in kilogram per output for all countries 9

10 Table 2: Largest environmental multipliers per material for the World Kilogram of additional domestic extraction per additional demand Rank Fossil fuel carriers Metals Minerals 1 i i i i i i i i i i i i i i i There is a large variation in the individual country multipliers as shown in Appendix 2 Table 2. For metals, the Czech Republic, Italy, Japan, Portugal, Slovenia and Taiwan have very small multipliers compared to the world average. Bulgaria, Cyprus, France, India, Indonesia and South Korea all require more than 100 kg metals per euro of extra final demand for sector i13; metal ores. About four times as much as the world average. For sector i27 all multipliers are due to embodied metals in the inputs bought by the sector. Large values are found for Australia, Bulgaria and Indonesia. Basic manufacturing of metals in these countries requires more metals per euro of final demand. The multipliers per country-sector can be broken into a domestic environmental multiplier and an international environmental multiplier. The international environmental multiplier as percentage of the total multiplier is a measure of the dependence of a country on foreign suppliers. It shows the share of additional demand for materials that has to be satisfied from suppliers abroad. The higher this percentage the more dependent a country is on foreign suppliers. In Appendix 2 the international multiplier percentage is given for each country for the five sectors that required, on a world scale, the most additional material resources when demand for its products increase. The tables in Appendix 2 also show the Herfindahl index (HI) calculated based on the international multipliers. A combination of a high international environmental multiplier combined with a high value for the Herfindahl index can indicate a vulnerable supplier relationship for a specific material resource and the sector that requires the material in its production process. Table 3 below shows the results for 30 countries that have relatively high percentages of international multipliers and high values of the Herfindahl index. Sector i23, manufacture of coke, refined petroleum products, and nuclear fuels has high values for these two indicators for all three material resources. 10

11 Table 3: Sector i23: Manufacture of coke, refined petroleum products, and nuclear fuels Fossil fuel carriers Metals Minerals inter % HI inter % HI inter % HI Austria Belgium Bulgaria Canada Cyprus Czech_Republic Denmark Finland France Germany Greece Hungary Italy Japan Latvia Malta Netherlands Poland Portugal Romania Slovak_Republic Slovenia South_Africa South_Korea Spain Sweden Switzerland Taiwan Turkey United_Kingdom From Table 3 it can be seen that most European countries have a high international multiplier percentage, which is consistent with the European open market. However, the Herfindahl index for the East-European countries is in general higher than the Herfindahl index for the West-European countries. The concentration of supplier relations is especially high for fossil fuel carriers, even though 35 of the countries included in the dataset extract fossil fuel carriers domestically. This would suggest that especially for Bulgaria, Czech Republic, Greece, Slovak Republic and Slovenia, it might be wise to diversify their supplier relations more. In Table 4 the coefficients of determination are presented. These values show for the five heavy use sectors for each of the three material groups how much of the variation in the one variable can be explained by the variation of the other. In other words, a high coefficient of 11

12 determination shows whether the total material multipliers (tm), the extent of international dependency (id) and the Herfindahl index (hi) of the international multipliers correlate over the countries. Table 4: Coefficients of determination as percentage (R 2 % of variation explained) Fossil fuel carriers Metals Minerals id hi id hi id hi i10 tm (-) i13 (-) i14 (-) 5.1 (-) 0.0 id i11 tm (-) i12 (-) i26 (-) id i23 tm i27 (-) i23 (-) id 10.4 (-) i40 tm (-) i i13 (-) id i12 tm i37 (-) i10 (-) id For two sectors there is a significant correlation between the total resource multiplier and international dependency. That some of the sectors are more exposed to international concentrated relations can be seen from the coefficients of determination for the international environmental dependency measure and the Herfindahl index of the international multipliers. For both fossil fuel carriers seem and metal resources supplier dependency can become an issue for sectors i12 Mining of uranium and thorium ores. 12

13 5. Conclusion and outlook These first results indicate that international dependency on material resource suppliers differs much from sector to sector. Especially for sectors that are of strategic importance to the functioning of the economy at large, it is important to investigate the extent of dependency and the concentration of dependency. A start of the analysis of dependency has been made in this paper, but the matter is definitely in need of further investigation. The EXIOPOL database will offer a wealth of information. Unfortunately not all of this information is available yet. The large differences in the environmental multipliers could be the result of the aggregation of the sectors, causing different products to be lumped together. For example, in the final EXIOPOL database sector i13; metal ores will be split into six different metal ore sectors. The aggregation bias of the results will be checked as soon as the more detailed data becomes available. 13

14 References Bouwmeester, M. C., & Oosterhaven, J. (2008). Methodology for the construction of an international supply-use table. Paper presented at the IIOA intermediate conference, Seville, Spain. Dimaranan, B. V. (2006). Global trade, assistance, and production: The GTAP 6 data base. West Lafayette, IN, USA: Center for Global Trade Analysis, Purdue University. Eder (ed), P., Delgado (ed), L., Neuwahl (ed), F., Tukker, A., Huppes, G., van Oers, L., & Heijungs, R. (2006). Environmentally extended input-output tables and models for europe. Spain: Joint Research Centre, Institute for Prospective Technological Studies (JRC-IPTS). Inomata, S., & Okamoto, N. (Eds.). (2006). How to make Asian input-output tables. Chiba, Japan: IDE-JETRO. Lenzen, M., Pade, L., & Munksgaard, J. (2004). CO 2 multipliers in multi-region input-output models. Economic Systems Research, 16(4), doi: / Linden, J.,A.van der, & Oosterhaven, J. (1995). European community intercountry input-output relations: Construction method and main results for Economic Systems Research, 7(3), Miller, R. E., & Blair, P. D. (1984). Input-output analysis: Foundations and extensions Prentice Hall. Tukker, A., Poliakov, E., Heijungs, R., Hawkins, T., Neuwahl, F., Rueda-Cantuche, J. M., Giljum, S., Moll, S., Oosterhaven, J., & Bouwmeester, M. (2009). Towards a global multi- 14

15 regional environmentally extended input-output database. Ecological Economics, 68(7), Wiedmann, T., Wood, R., Lenzen, M., Minx, J., Guan, D., & Barrett, J. (2008). Development of an embedded carbon emissions indicator - producing a time series of input-output tables and embedded carbon dioxide emissions for the UK by using a MRIO data optimisation system Report to the UK Department for Environment, Food and Rural Affairs by Stockholm Environment Institute at the University of York and Centre for Integrated Sustainability Analysis at the University of Sydney, Defra, Londen, UK. Wiedmann, T. (2009). A review of recent multi-region input-output models used for consumption-based emission and resource accounting. Ecological Economics, 69(2),

16 Appendix 1: sector classification 16

17 Appendix 2: additional result tables Table 1: Domestic extraction used kilogram per output by country, ordered Note: 0 means no value. 17

18 Table 2: Environmental multipliers by country kilogram per demand Note: 0 means no value. 18

19 Table 3: International environmental multiplier as % of total environmental multiplier Herfindahl index of international multipliers Fossil fuel carriers Note: - means no value, 0 indicates a value smaller than

20 Table 4: International environmental multiplier as % of total environmental multiplier Herfindahl index of international multipliers Metals Note: - means no value, 0 indicates a value smaller than

21 Table 5: International environmental multiplier as % of total environmental multiplier Herfindahl index of international multipliers Minerals 21